GRAB.SimuPheno

<code>GRAB</code> package can help simulate a wide variaty of phenotypes

Provides a comprehensive suite of genome-wide association study (GWAS) methods
specifically designed for biobank-scale data. The package offers computationally efficient
and robust association tests for time-to-event traits (e.g., Bi et al., 2020
<doi:10.1016/j.ajhg.2020.06.003>), ordinal categorical traits (e.g., Bi et al., 2021
<doi:10.1016/j.ajhg.2021.03.019>), and longitudinal traits (Xu et al., 2025
<doi:10.1038/s41467-025-56669-1>). Additionally, it includes functions for
simulating genotype and phenotype data to support research and method development.

Woody Miao

GRAB

Genome-Wide Robust Analysis for Biobank Data (GRAB)

Wenjian Bi

Wei Zhou

Rounak Dey

Zhangchen Zhao

Seunggeun Lee

GRAB.SimuPheno function

<dl><dt>eta</dt>
<dd>linear predictors, usually covar x beta.covar + genotype x beta.genotype</dd>
<dt>traitType</dt>
<dd>"quantitative", "binary", "ordinal", or "time-to-event"</dd>
<dt>control</dt>
<dd>a list of parameters for controlling the simulation process</dd>
<dt>seed</dt>
<dd>a random number seed for reproducibility</dd></dl>

Arguments

Simulate phenotype using linear predictor eta — GRAB.SimuPheno

<dl>

<dt>eta</dt>
<dd>linear predictors, usually covar x beta.covar + genotype x beta.genotype</dd>


<dt>traitType</dt>
<dd>"quantitative", "binary", "ordinal", or "time-to-event"</dd>


<dt>control</dt>
<dd>a list of parameters for controlling the simulation process</dd>


<dt>seed</dt>
<dd>a random number seed for reproducibility</dd>

</dl>

GRAB.SimuPheno: Simulate phenotype using linear predictor `eta`

Description

Usage

Value

Arguments

Details